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Abstract Magnetic skyrmions, which are stable, topologically protected spin structures, have garnered significant interest for their potential in revolutionizing spintronic applications. This study reveals the room‐temperature coexistence of Néel‐type and Bloch‐Néel hybrid skyrmions in [Pt/Co/Cu] multilayers grown by molecular beam epitaxy (MBE). Pulse current is used to switch the skyrmion type and modulate the stability of the skyrmions. The thermal effect on the stability of the skyrmions due to the current pulse is also investigated. The work unveils a broad magnetic phase space, offering unprecedented control over skyrmion states in metallic multilayers with broken inversion symmetry. These findings pave the way for diverse applications in spintronics, including binary data encoding, and provide a novel framework for the manipulation of multi‐type skyrmions. 

Abstract Topological magnons give rise to possibilities for engineering novel spintronics devices with critical applications in quantum information and computation, due to their symmetry-protected robustness and low dissipation. However, to make reliable and systematic predictions about the material realization of topological magnons has been a major challenge, due to the lack of neutron scattering data for most materials and the absence of reliable ab initio calculations for magnons. In this work, we significantly advance the symmetry-based approach for identifying topological magnons through developing a fully automated algorithm, utilizing the theory of symmetry indicators, that enables a highly efficient and large-scale search for candidate materials hosting perturbation-driven topological magnons. This progress not only streamlines the discovery process but also expands the scope of materials exploration beyond previous manual or traditional approaches, offering a powerful tool for uncovering novel topological phases in magnetic systems. Performing a large-scale search over all 1649 magnetic materials in the Bilbao Crystallographic Server (BCS) with a commensurate magnetic order, we discover 387 perturbation-induced topological magnon materials, significantly expanding the pool of topological magnon materials and showing that more than 23% of all commensurate magnetic compounds in the BCS database are topological. We further discuss examples and experimental accessibility of the candidate materials, shedding light on future experimental realizations of topological magnons in magnetic materials. We provide anopen-source programthat checks the symmetry-enforced magnon band topology of any commensurate magnetic structure upon perturbations and allows researchers to reproduce our results. 

Abstract Nature provides many examples of the benefits of nanoscopic surface structures in areas of adhesion and antifouling. Herein, the design, fabrication, and characterization of liquid crystal elastomer (LCE) films are presented with nanowire surface structures that exhibit tunable stimuli‐responsive deformations and enhanced adhesion properties. The LCE films are shown to curl toward the side with the nanowires when stimulated by heat or organic solvent vapors. In contrast, when a droplet of the same solvent is placed on the film, it curls away from the nanowire side due to nanowire‐induced capillary forces that cause unequal swelling. This characteristic curling deformation is shown to be reversible and can be optimized to match curved substrates, maximizing adhesive shear forces. By using chemical modification, the LCE nanowire films can be given underwater superoleophobicity, enabling oil repellency under a range of harsh conditions. This is combined with the nanowire‐induced frictional asymmetry and the reversible shape deformation to create an underwater droplet mixing robot, capable of performing chemical reactions in aqueous environments. These findings demonstrate the potential of nanowire‐augmented LCE films for advanced applications in soft robotics, adaptive adhesion, and easy chemical modification, with implications for designing responsive materials that integrate mechanical flexibility with surface functionality. 

Abstract In the burgeoning field of spintronics, antiferromagnetic materials (AFMs) are attracting significant attention for their potential to enable ultra‐fast, energy‐efficient devices. Thin films of AFMs are particularly promising for practical applications due to their compatibility with spin‐orbit torque (SOT) mechanisms. However, studying these thin films presents challenges, primarily due to the weak signals they produce and the rapid dynamics driven by SOT, that are too fast for conventional electric transport or microwave techniques to capture. The time‐resolved magneto‐optical Kerr effect (TR‐MOKE) has been a successful tool for probing antiferromagnetic dynamics in bulk materials, thanks to its sub‐picosecond (sub‐ps) time resolution. Yet, its application to nanometer‐scale thin films has been limited by the difficulty of detecting weak signals in such small volumes. In this study, the first successful observation of antiferromagnetic dynamics are presented in nanometer‐thick orthoferrite films using the pump‐probe technique to detect TR‐MOKE signal. This paper report an exceptionally low damping constant of 1.5 × 10⁻⁴and confirms the AFM magnonic nature of these dynamics through angular‐dependent measurements. Furthermore, it is observed that electrical currents can potentially modulate these dynamics via SOT. The findings lay the groundwork for developing tunable, energy‐efficient spintronic devices, paving the way for advancements in next‐generation spintronic applications. 

Abstract With rapid progress in simulation of strongly interacting quantum Hamiltonians, the challenge in characterizing unknown phases becomes a bottleneck for scientific progress. We demonstrate that a Quantum-Classical hybrid approach (QuCl) of mining sampled projective snapshots with interpretable classical machine learning can unveil signatures of seemingly featureless quantum states. The Kitaev-Heisenberg model on a honeycomb lattice under external magnetic field presents an ideal system to test QuCl, where simulations have found an intermediate gapless phase (IGP) sandwiched between known phases, launching a debate over its elusive nature. We use the correlator convolutional neural network, trained on labeled projective snapshots, in conjunction with regularization path analysis to identify signatures of phases. We show that QuCl reproduces known features of established phases. Significantly, we also identify a signature of the IGP in the spin channel perpendicular to the field direction, which we interpret as a signature of Friedel oscillations of gapless spinons forming a Fermi surface. Our predictions can guide future experimental searches for spin liquids. 

Abstract Two-dimensional (2D) superlattices, formed by stacking sublattices of 2D materials, have emerged as a powerful platform for tailoring and enhancing material properties beyond their intrinsic characteristics. However, conventional synthesis methods are limited to pristine 2D material sublattices, posing a significant practical challenge when it comes to stacking chemically modified sublattices. Here we report a chemical synthesis method that overcomes this challenge by creating a unique 2D graphene superlattice, stacking graphene sublattices with monodisperse, nanometer-sized, square-shaped pores and strategically doped elements at the pore edges. The resulting graphene superlattice exhibits remarkable correlations between quantum phases at both the electron and phonon levels, leading to diverse functionalities, such as electromagnetic shielding, energy harvesting, optoelectronics, and thermoelectrics. Overall, our findings not only provide chemical design principles for synthesizing and understanding functional 2D superlattices but also expand their enhanced functionality and extensive application potential compared to their pristine counterparts. 

Abstract Cr_xPt_1−xTe₂is a recently developed van der Waals magnetic alloy noted for its stability under ambient conditions. Here, we report the emergence of an exchange bias effect in Cr_xPt_1−xTe₂, without typical exchange bias sources such as an adjacent antiferromagnetic layer. We find that the exchange bias is present forx = 0.45 and absent forx = 0.35, which is correlated to the presence of a Cr modulation where the Cr concentration alternates each vdW layer (modulation period of 2 layers) forx ≥ 0.4. We perform Monte Carlo simulations utilizing exchange parameters from first-principles calculations, which recreate the exchange bias in hysteresis loops of Cr_0.45Pt_0.55Te₂. From our simulations, we infer the source of exchange bias to be magnetic moments locked into free energy minima that resist magnetization reversal. This work presents a way to introduce desirable magnetic properties to van der Waals magnets. 

Abstract Harnessing electronic excitations involving coherent coupling to bosonic modes is essential for the design and control of emergent phenomena in quantum materials. In situations where charge carriers induce a lattice distortion due to the electron-phonon interaction, the conducting states get “dressed, which leads to the formation of polaronic quasiparticles. The exploration of polaronic effects on low-energy excitations is in its infancy in two-dimensional materials. Here, we present the discovery of an interlayer plasmon polaron in heterostructures composed of graphene on top of single-layer WS₂. By using micro-focused angle-resolved photoemission spectroscopy during in situ doping of the top graphene layer, we observe a strong quasiparticle peak accompanied by several carrier density-dependent shake-off replicas around the single-layer WS₂conduction band minimum. Our results are explained by an effective many-body model in terms of a coupling between single-layer WS₂conduction electrons and an interlayer plasmon mode. It is important to take into account the presence of such interlayer collective modes, as they have profound consequences for the electronic and optical properties of heterostructures that are routinely explored in many device architectures involving 2D transition metal dichalcogenides. 

Abstract Structural domains and domain walls, inherent in single crystalline perovskite oxides, can significantly influence the properties of the material and therefore must be considered as a vital part of the design of the epitaxial oxide thin films. We employ 4D-STEM combined with machine learning (ML) to comprehensively characterize domain structures at both high spatial resolution and over a significant spatial extent. Using orthorhombic LaFeO₃as a model system, we explore the application of unsupervised and supervised ML in domain mapping, which demonstrates robustness against experiment uncertainties. The results reveal the consequential formation of multiple domains due to the structural degeneracy when LaFeO₃film is grown on cubic SrTiO₃. In situ annealing of the film shows the mechanism of domain coarsening that potentially links to phase transition of LaFeO₃at high temperatures. Moreover, synthesis of LaFeO₃on DyScO₃illustrates that a less symmetric orthorhombic substrate inhibits the formation of domain walls, thereby contributing to the mitigation of structural degeneracy. High fidelity of our approach also highlights the potential for the domain mapping of other complicated materials and thin films. 

Abstract Glutamate is one of the most important excitatory neurotransmitters within the mammalian central nervous system. The role of glutamate in regulating neural network signaling transmission through both synaptic and extra‐synaptic paths highlights the importance of the real‐time and continuous monitoring of its concentration and dynamics in living organisms. Progresses in multidisciplinary research have promoted the development of electrochemical glutamate sensors through the co‐design of materials, interfaces, electronic devices, and integrated systems. This review summarizes recent works reporting various electrochemical sensor designs and their applicability as miniaturized neural probes to in vivo sensing within biological environments. We start with an overview of the role and physiological significance of glutamate, the metabolic routes, and its presence in various bodily fluids. Next, we discuss the design principles, commonly employed validation models/protocols, and successful demonstrations of multifunctional, compact, and bio‐integrated devices in animal models. The final section provides an outlook on the development of the next generation glutamate sensors for neuroscience and neuroengineering, with the aim of offering practical guidance for future research.